itsmuriuki/FIFA-2018-World-cup-predictions
I used Machine Learning to make a Logistic Regression model using scikit-learn, pandas, numpy, seaborn and matplotlib to predict the results of FIFA 2018 World Cup. (⭐ 166)
I used Machine Learning to make a Logistic Regression model using scikit-learn, pandas, numpy, seaborn and matplotlib to predict the results of FIFA 2018 World Cup. (⭐ 166)
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Wayback Machine (archived 2016-11-11) Shamir, Adi (October 1976). The fixedpoints of recursive definitions. Weizmann Institute of Science. OCLC 884951223
This study explores a Bayesian algorithmic approach to personalized fragrance recommendation by integrating hierarchical Relevance Vector Machines (RVM) and Jungian personality archetypes. The paper proposes a structured model that links individual s...
Built a fragrance recommender using multiple machine learning algorithms to help people find their perfect match. The final deliverable was a webapp. (⭐ 117)
This research introduces a Machine Learning-centric approach to replicate olfactory experiences, validated through experimental quantification of perfume perception. Key contributions encompass a hybrid model connecting perfume molecular structure to...
Machine learning Fantasy Premier League team (⭐ 339)
Machine learning methodologies can be adopted in cultural applications and propose new ways to distribute or even present the cultural content to the public. For instance, speech analytics can be adopted to automatically generate subtitles in theatri...
While deep learning has catalyzed breakthroughs across numerous domains, its broader adoption in clinical settings is inhibited by the costly and time-intensive nature of data acquisition and annotation. To further facilitate medical machine learning...
Accurate assessment of dietary intake requires improved tools to overcome limitations of current methods including user burden and measurement error. Emerging technologies such as image-based approaches using advanced machine learning techniques coup...
Mapping Philippine Poverty using Machine Learning, Satellite Imagery, and Crowd-sourced Geospatial Information (⭐ 84)
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T (⭐ 4449)
Sep 19, 2025 · Using generative AI to help robots jump higher and land safely MIT CSAIL researchers combined GenAI and a physics simulation engine to refine robot designs. The result: a machine that …
the process or state of acting or of being active. The machine is not in action now. something done or performed; act; deed. an act that one consciously wills and that may be characterized by physical or …
**RenalNet** is an end-to-end machine learning solution designed to predict renal failure from ultrasound images. This project leverages advanced deep learning techniques, custom data augmentation, and robust training strategies to build a clinical diagnostic…
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Machine-learned interatomic potentials enable large systems to be simulated for long time scales at near ab-initio accuracy. This accuracy is achieved by fitting extremely flexible model architectures to high quality reference data. In practice, this...
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optim…
the process or state of acting or of being active. The machine is not in action now. something done or performed; act; deed. an act that one consciously wills and that may be characterized by physical or …
Adjective unanswered (not comparable) That has not been answered or addressed. The flashing light on the answering machine bore testimony to the unanswered call.